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ABET Course Syllabus
Course Title
Artificial Intelligence
Course Number
Total Credit
CS 460
4
Coordinator
Russ Abbott
Contact Hours
4 hours/week
Course Information
This course is an elective in the BS programs.
a) Catalog Description
Knowledge representation; problem solving strategies and search algorithms;
applications from such areas as theorem proving, expert systems, natural language
processing, robotics, and pattern recognition.. Lecture 3 hours, recitation/activity 1
hour.
b) Prerequisite: CS 312. Corequisite: CS 332 and CS 370.
Course Goals
At the end of the course, students are able to

Understand and explain the differences between problems that require artificial
intelligent techniques and those that can be solved directly.

Understand, explain, implement, and apply a wide range of search algorithms.

Make use of a range of knowledge representation strategies.

Understand and use constraint processing systems.
The Student Learning Outcomes that are addressed by the course are SLO1, SLO2, and
SLO3.
SLO #1. Students will be able to apply concepts and techniques from computing and
mathematics to both theoretical and practical problems.
SLO #2. Students will be able to demonstrate fluency in at least one programming
language and acquaintance with at least three more.
SLO #3. Students will have a strong foundation in the design, analysis, and
application of many types of algorithms.
Major Topics Covered in the Course:
 Intelligent agents
 Search
 Knowledge and Reasoning
 Planning
 Constraint programming
Recitation sections
Hands-on activities are critical components of computer science courses that have
significant programming components. Each week students do a project related to the
week’s material. During the recitation section, students describe and explain their
work. Explaining what one has done helps develop a deeper understanding of it.
Besides pushing them to deepen their understanding, the explanation requirement
helps students develop presentation skills they will need after graduation.
Textbook
Russell, S and P. Norvig, Artificial Intelligence a Modern Approach.
References
Barrat, James (2013) Our Final Invention: Artificial Ingelligence and the End of the
Human Era. Thomas Dunne Books.
Floreano, Dario and Claudio Mattiussi (2008) Bio-Inspired Artificial Intelligence:
Theories, Methjods, and Technologies. MIT Press.
Kelly, John E. III (2013) Smart Machines: IBM’s Watson and the Era of Cognitive
Computing. Columbia University Press.
Kurzweil, Ray (2013) How to Create a Mind: The Secret of Human Thought Revealed.
Penguin Books.
Jones, Tim (2007) Artificial Intelligence: A Systems Approach. Jones and Bartlett.
Lucci, Steven (2012) Artificial Intelligence in the 21st Century. Mercury Learning and
Information
Luger, George F. (2008) AI Algorithms, Data Structures and Idoms in Prolog, List,
and Java. Addison-Wesley.
Luger, George F. and Willian A. Stubblefield (2008) Artificial Intelligence: Structures
and Strategies for Complex Problem Solving. Addison-Wesley.
Millington, Ian and John Munge (2009) Artificial Intelligence for Games. CRC Press.
Nilsson, Nils J. (2009) The Quest for Artificial Intelligence. Cambridge University
Press.
Poole, David L. and Alan K. Mackworth (2010) Artificial Intelligence: Foundations of
Computational Agents. Cambridge University Press.
Warwick, Kevin, (2011) Artificial Intelligence: The Basics. Routledge.
Assessment
[(i) Chengyu and I will send you the list of courses that this section is applicable. (ii) We
will include the necessary assignments/projects/rubrics that will be applied in this course
that gives the data for direct measures described in the assessment plan]
Academic Integrity
Cheating will not be tolerated. Anyone cheating or helping someone else cheat will
receive a grade of F for the course and will be reported to the proper authorities.
ADA Statement
Reasonable accommodation will be provided to any student who is registered
with the Office of Students with Disabilities and requests needed
accommodation.